With expected high penetration of broadband wireless networks based on technologies such as Long Term Evolution (LTE) and WiMAX and extensive deployment of multimedia services such as Video on Demand (VoD) or Internet Protocol television (IPTV), video streaming applications will increase significantly. As a result, wireless subscribers would increasingly use their mobile devices to access video content on the internet. Furthermore, streaming real-time video in wireless networks usually requires relatively high Quality of Service (QoS) due to the stringent service requirements of video applications. Therefore, service providers are confronted with the problem of efficient resource allocation when providing video streaming applications for their end users.
Efficient allocation of resources for video streaming applications in wireless networks is a challenging problem. One conventional solution is rate adaptive video streaming. Most of the rate adaptive solutions assume that a video server receives feedback information such as end-to-end delay or loss rate from the end user. By using the feedback information, the video server may choose an optimum coding option. However, the rate adaptive solution may not be feasible in wireless networks for video streaming because the system employing the rate adaptive solution may not be able to track fast changes in the communication channel. Moreover, the rate adaptive solution increases the computational complexity at the video server which may result in overloading the video server in large networks. Furthermore, sending feedback information may not be possible in some video streaming applications such as IPTV in which the video server has to multicast the same video content to different users.
One of the issues for streaming real-time video over wireless networks is sustaining satisfactory video quality even when congestion occurs or the wireless communication channels become less reliable. Different conventional techniques have been proposed to achieve an acceptable video quality with respect to the limited network resources. However, irrespective of the type of conventional technique, video packets will be inevitably lost due to transmission errors over the wireless communication channels or dropped due to overflow of a transmit buffer at a base station in a wireless network. Video packet loss affects video quality of the video content being streamed over the wireless network. Although error moderating schemes such as rate adaptive coding, forward error correction schemes, and scalable video coding have been utilized to mitigate the effects of video degradation due to packet loss, these conventional approaches increase the complexity at the video server, which requires more allocated resources in a resource scarce environment.